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Grounding language in action and perception: from cognitive agents to humanoid robots
1Centre for Robotics and Neural Systems, University of Plymouth, UK. acangelosi@plymouth.ac.uk
Physics of Life Reviews
|April 27, 2010
Summary
This review explores how cognitive agents and developmental robotics model language acquisition using symbol grounding. It highlights the benefits for creating robotic agents with linguistic capabilities.
Area of Science:
- Cognitive Science
- Robotics
- Developmental Psychology
- Artificial Intelligence
Background:
- Theories of language acquisition often lack grounding in embodied, developmental processes.
- Modeling cognition requires integrating sensorimotor experiences with linguistic development.
- Developmental robotics offers a framework for studying embodied cognition and language evolution.
Purpose of the Study:
- To review grounded approaches to modeling cognition using cognitive agents and developmental robotics.
- To focus on the evolutionary and developmental acquisition of linguistic capabilities based on symbol grounding principles.
- To demonstrate the consistency of these models with empirical evidence and highlight their benefits for robotic agents.
Main Methods:
- Review of existing cognitive agent and developmental robotics models.
- Analysis of models focusing on symbol grounding and language acquisition.
- Discussion of three models with increasing system complexity: multi-agent simulation, simulated robotic agent, and humanoid robot (iCub).
Main Results:
- Cognitive agent and developmental robotics models align with empirical and theoretical evidence on language grounding and embodiment.
- These approaches offer significant benefits for designing linguistic capabilities in cognitive robotic agents.
- The review details progressive models, from evolutionary simulations to embodied language comprehension in humanoid robots.
Conclusions:
- Grounded approaches in cognitive agents and developmental robotics are crucial for understanding language acquisition.
- Humanoid robotic platforms, like the open-source iCub, are valuable for studying embodied cognition and language.
- This research provides a foundation for developing more sophisticated linguistic abilities in artificial agents.
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